In the state of the art, an earthquake prediction system or an earthquake damage prediction system is a system capable of generating prediction that an earthquake of a specific magnitude will occur in a particular place at a particular time (or ranges thereof) and which damage it will cause to what kind of objects, respectively. Despite considerable research and development efforts by engineer and seismologists, scientifically reproducible predictions are difficult to make and cannot yet be made to a specific hour, day, or month. Only for well-understood geological faults, seismic hazard assessment maps can estimate the probability that an earthquake of a given size will affect a given location over a certain number of years and what kind of damage it can cause to different structured objects at that location. Once an earthquake has already begun, there are early warning devices in the state of the art which can provide a few seconds' warning before major shaking arrives at a given location. This technology takes advantage of the different speeds of propagation of the various types of vibrations produced. Aftershocks are also likely after a major quake, and are commonly planned for in earthquake disaster response protocols.
Experts do advise general earthquake preparedness, especially in areas known to experience frequent or large quakes, to prevent injury, death, and property damage if a quake occurs with or without warning. To have the proper preparedness, it is necessary to predict the impact of a possible earthquake to the objects placed at the location. In the state of the art, the systems use so called earthquake impact (or damage) index to quantitatively approximate the impact or damage caused by an earthquake to a pre-defined object or even portfolio of objects or of values of property or non-property nature, associated with different geographical locations, e.g. damages relating to buildings, bridges, highways, power lines, communication lines, manufacturing plants or power plants, but also non-physical values, e.g. business interruption, contingent business interruption values or exposed population, based solely on physically measured and publicly available parameters of the earthquake phenomenon itself. The impact index parameters can then by used to electronically generate appropriate alarm or activation signals, which can be transmitted to correlated modules and alarm devices.
An earthquake impact index parameter is usually based on a pre-defined set of rules and can be assessed immediately after the earthquake. Defining the earthquake impact index solely on a measured magnitude of the earthquake has the disadvantage that there is no consideration of the portfolio and its geographical distribution of objects. Consequently, an earthquake impact index based solely on the magnitude of the earthquake correlates poorly with the true damage caused to the assets (objects) included in the portfolio. Particularly, with an increase of the geographical area in which the geographical locations are distributed, the magnitude based impact index shows an increasingly poor correlation with the true damage. Thus, other methods use other physical parameters of an earthquake occurrence than magnitude, i.e. earthquake shaking intensity in form of peak ground acceleration or peak ground velocity. Such parameters depict in areas of the world equipped with a dense net of seismograph stations a map of the aerial extent of earthquake shaking intensity, rat her than only a single point measurement of the magnitude. Combining the aerial extent of earthquake shaking intensity with the distributed portfolio of objects allows for a much better correlation of the thus deducted earthquake impact index with really occurred impact or damage to the portfolio, while not sacrificing the immediateness of applicability after the event, as well as transparency to anyone willing to set up the computing procedure. However, owing to the cost of installation and maintenance, an infrastructure with a network of geographically densely distributed seismological measurement stations is currently not available in the majority of countries.
In the effort to predict earthquakes, engineers have tried to associate an impending earthquake with such varied phenomena as seismicity patterns, electromagnetic fields, ground movement, weather conditions and unusual clouds, radon or hydrogen gas content of soil or ground water, water level in wells, animal behavior, and the phases of the moon. Many pseudoscientific theories and predictions are made, which scientific practitioners find problematic. The natural randomness of earthquakes and frequent activity in certain areas can be used to make “predictions” which may generate unwarranted credibility. These generally leave certain details unspecified, increasing the probability that the vague prediction criteria will be met, and ignore quakes that were not predicted. However, even if the prediction models are comparatively good, the propagation through different geological structures is difficult to determine and to weight within a certain region. In the state of the at there are official earthquake prediction evaluation councils which have been established e.g. in California (the California Earthquake Prediction Evaluation Council) and the federal government in the United States (the National Earthquake Prediction Evaluation Council), but have yet to endorse any method of predicting quakes as reliable. Technological evaluations methods of prediction look for the following input elements for a method: A specific location or area, a specific span of time, a specific magnitude range and/or specific probability of occurrence. Attribution to a plausible physical mechanism lends credibility, and suggests a means for future improvement. Reproducibility and statistical analysis are used to distinguish predictions, which come true due to random chance (of which a certain number are expected) versus those that have more useful predictive capability, and to validate models of long-term probability. Such models are difficult to test or validate because large earthquakes are so rare, and because earthquake activity is naturally clustered in space and time. “Predictions” which are made only after the fact are common but generally discounted.
Known prediction models in the state of the art are e.g. the emission of radon as a quake precursor. This method has still no reliable results. It is under study at NASA as of 2009. VAN is another method of earthquake prediction in the state of the art proposed by Professors Varotsos, Alexopoulos and Nomicos in the 1980s. The method is based on the detection of “seismic electric signals” (SES) via a telemetric network of conductive metal rods inserted in the ground. The method stems from theoretical predictions by P. Varotsos, a solid-state physicist at the National and Capodistrian University of Athens. It is continually refined as to the manner of identifying SES from within the abundant electric noise the VAN sensors are picking up. Researchers have claimed to be able to predict earthquakes of magnitude larger than 5, within 100 km of epicentral location, within 0.7 units of magnitude and in a 2-hour to 11-day time window. Other systems are based on measuring foreshocks, which are medium-sized earthquakes that precede major quakes. An increase in foreshock activity (combined with purported indications like ground water levels and strange animal behavior) enabled the successful evacuation a million people one day before the Feb. 4, 1975 M7.3 Haicheng earthquake by the China State Seismological Bureau. While 50% of major earthquakes are preceded by foreshocks, only about 5-10% of small earthquakes turn out to be foreshocks, leading to many false warnings. According to new systems and method by Prof. Shlomo Havlin, of Bar-Ilan University's Department of Physics, earthquakes form patterns, which can improve the ability to predict the timing of their recurrence. These systems use the “scaling” approach from physics to develop a mathematical based method to characterize earthquakes of a wide range of magnitudes whereas smaller magnitude earthquakes parameter serve as input values or initial start parameter to generate predictions about larger magnitude earthquakes. The method proposes that the recurrence of earthquakes is strongly dependent on the recurrence times of previous earthquakes. This memory effect used in the method not only provides a clue to understanding the observed clustering of earthquakes, but also suggests that delays in earthquake occurrences, as seen today in Tokyo and in San Francisco, are a natural phenomenon. One other possible method for predicting earthquakes is based on fractoluminescence. The method measures flashes of red and blue light in the sky, which accumulate often up to an hour before the earthquake. Studies have shown that upon fracturing, silica releases red and blue light for a period of about 100 milliseconds. This is attributed to the relaxation of the free bonds and unstable oxygen atoms that are left when the silicon oxygen bonds have broken due to the stresses within the rock. Finally, some methods relay on the detection of electro-magnetic emissions transmitted from earthquake regions by satellite. These systems use the fact that there have been observed strong correlations between certain types of low frequency electromagnetic activity and the seismically most active zones on the Earth. For example there was a sharp signal in the ionospheric electron density and temperature near southern Japan seven days before a 7.1 magnitude occurred there. In the state of the art, there are still other early warning systems and damage prediction systems not mentioned here. As further example may serve the patent documents JP60014316, GR1003604, GR96100433, CN1547044, JP2008165327, JP2008077299, US 2009/0164256 or US 2009/0177500. In the state of the art, efficient earthquake damage prediction and prevention systems are technically difficult to realize. They can comprise e.g. earthquake detection units or method together with units to generate propagate values of the earthquake's hypocenter or epicenter. Even within an epicenter region it is often difficult to properly weight the local impact and impact values, respectively, due to different geological formations, gating of the affected object to the ground and internal structure and assembly of the affected object. However, quickly knowing the impact of the earthquake to affected objects within a region can be important to generate and transmit correct activation signals or alarm signals to e.g. automated emergency devices or damage intervention devices or systems and/or general operating malfunction intervention devices, as for instance, monitoring devices, alarm devices or systems for direct technical intervention at the affected object. Furthermore, earthquake damage prediction and prevention systems of the date of art are not very reliable and often to slow. One of the problems of the state of the art is, that the signals of the systems can hardly be correctly weight, due to the law of large numbers i.e. of low statistic in the field of earthquakes in connection with a specific geological formation. Finally, those systems of the state of the art are expensive to realize and extremely costly in terms of labor.